Also note that the collections library was carefully designed to include several implementations of
each of the three basic collection types. These implementations have specific performance
characteristics which are described
in the guide.

This is a base trait for Scala parallel collections. It defines behaviour
common to all parallel collections. Concrete parallel collections should
inherit this trait and ParIterable if they want to define specific combiner
factories.

Parallel operations are implemented with divide and conquer style algorithms that
parallelize well. The basic idea is to split the collection into smaller parts until
they are small enough to be operated on sequentially.

All of the parallel operations are implemented as tasks within this trait. Tasks rely
on the concept of splitters, which extend iterators. Every parallel collection defines:

def splitter: IterableSplitter[T]

which returns an instance of IterableSplitter[T], which is a subtype of Splitter[T].
Splitters have a method remaining to check the remaining number of elements,
and method split which is defined by splitters. Method split divides the splitters
iterate over into disjunct subsets:

def split: Seq[Splitter]

which splits the splitter into a sequence of disjunct subsplitters. This is typically a
very fast operation which simply creates wrappers around the receiver collection.
This can be repeated recursively.

Method newCombiner produces a new combiner. Combiners are an extension of builders.
They provide a method combine which combines two combiners and returns a combiner
containing elements of both combiners.
This method can be implemented by aggressively copying all the elements into the new combiner
or by lazily binding their results. It is recommended to avoid copying all of
the elements for performance reasons, although that cost might be negligible depending on
the use case. Standard parallel collection combiners avoid copying when merging results,
relying either on a two-step lazy construction or specific data-structure properties.

Methods:

def seq: Sequential
def par: Repr

produce the sequential or parallel implementation of the collection, respectively.
Method par just returns a reference to this parallel collection.
Method seq is efficient - it will not copy the elements. Instead,
it will create a sequential version of the collection using the same underlying data structure.
Note that this is not the case for sequential collections in general - they may copy the elements
and produce a different underlying data structure.

The combination of methods toMap, toSeq or toSet along with par and seq is a flexible
way to change between different collection types.

Since this trait extends the GenIterable trait, methods like size must also
be implemented in concrete collections, while iterator forwards to splitter by
default.

Each parallel collection is bound to a specific fork/join pool, on which dormant worker
threads are kept. The fork/join pool contains other information such as the parallelism
level, that is, the number of processors used. When a collection is created, it is assigned the
default fork/join pool found in the scala.parallel package object.

Parallel collections are not necessarily ordered in terms of the foreach
operation (see Traversable). Parallel sequences have a well defined order for iterators - creating
an iterator and traversing the elements linearly will always yield the same order.
However, bulk operations such as foreach, map or filter always occur in undefined orders for all
parallel collections.

Existing parallel collection implementations provide strict parallel iterators. Strict parallel iterators are aware
of the number of elements they have yet to traverse. It's also possible to provide non-strict parallel iterators,
which do not know the number of elements remaining. To do this, the new collection implementation must override
isStrictSplitterCollection to false. This will make some operations unavailable.

To create a new parallel collection, extend the ParIterable trait, and implement size, splitter,
newCombiner and seq. Having an implicit combiner factory requires extending this trait in addition, as
well as providing a companion object, as with regular collections.

Method size is implemented as a constant time operation for parallel collections, and parallel collection
operations rely on this assumption.

The higher-order functions passed to certain operations may contain side-effects. Since implementations
of bulk operations may not be sequential, this means that side-effects may not be predictable and may
produce data-races, deadlocks or invalidation of state if care is not taken. It is up to the programmer
to either avoid using side-effects or to use some form of synchronization when accessing mutable data.

Equivalent to x.hashCode except for boxed numeric types and null.
For numerics, it returns a hash value which is consistent
with value equality: if two value type instances compare
as true, then ## will produce the same hash value for each
of them.
For null returns a hashcode where null.hashCode throws a
NullPointerException.

Note that the success of a cast at runtime is modulo Scala's erasure semantics.
Therefore the expression 1.asInstanceOf[String] will throw a ClassCastException at
runtime, while the expression List(1).asInstanceOf[List[String]] will not.
In the latter example, because the type argument is erased as part of compilation it is
not possible to check whether the contents of the list are of the requested type.

Tests whether the argument (that) is a reference to the receiver object (this).

Tests whether the argument (that) is a reference to the receiver object (this).

The eq method implements an equivalence relation on
non-null instances of AnyRef, and has three additional properties:

It is consistent: for any non-null instances x and y of type AnyRef, multiple invocations of
x.eq(y) consistently returns true or consistently returns false.

For any non-null instance x of type AnyRef, x.eq(null) and null.eq(x) returns false.

null.eq(null) returns true.

When overriding the equals or hashCode methods, it is important to ensure that their behavior is
consistent with reference equality. Therefore, if two objects are references to each other (o1 eq o2), they
should be equal to each other (o1 == o2) and they should hash to the same value (o1.hashCode == o2.hashCode).

returns

true if the argument is a reference to the receiver object; false otherwise.

Note that the result of the test is modulo Scala's erasure semantics.
Therefore the expression 1.isInstanceOf[String] will return false, while the
expression List(1).isInstanceOf[List[String]] will return true.
In the latter example, because the type argument is erased as part of compilation it is
not possible to check whether the contents of the list are of the specified type.

returns

true if the receiver object is an instance of erasure of type T0; false otherwise.

Body of the task - non-divisible unit of work done by this task.
Optionally is provided with the result from the previous completed task
or None if there was no previous task (or the previous task is uncompleted or unknown).

Creates a String representation of this object. The default
representation is platform dependent. On the java platform it
is the concatenation of the class name, "@", and the object's
hashcode in hexadecimal.